1. Joint Modeling
1.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
1.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.01
## LDevsum 1.00 1.02
## dh0 1.06 1.20
## dh1 1.02 1.05
## dh2 1.01 1.07
## dh3 1.00 1.00
## dl0 1.01 1.07
## dl1 1.00 1.02
##
## Multivariate psrf
##
## 1.04
1.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
1.4 WAIC results
| LevelH | LevelL | |
|---|---|---|
| DIC | 1212.29743 | 22623.1423 |
| DIC3 | 1153.34986 | 22720.6989 |
| PWAIC | 41.91931 | 259.5071 |
| WAIC | 1179.62499 | 22743.8827 |
2. Separate Modeling of High-Level
2.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
2.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## HDevsum 1.00 1.00
## dh0 1.02 1.08
## dh1 1.04 1.18
## dh2 1.13 1.48
## dh3 1.00 1.00
##
## Multivariate psrf
##
## 1.09
2.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
2.4 WAIC results
| H4 | |
|---|---|
| DIC | 1356.22810 |
| DIC3 | 1234.82456 |
| PWAIC | 86.20612 |
| WAIC | 1301.05551 |
3. Separate Modeling for Low-level
3.1 Trace plots for convergence check
The current MCMC setting is:
- 4000000 iteration;
- 3000000 burn-in;
- 1000 thinning.
3.2 Gelman and Rubin’s convergence check
## Potential scale reduction factors:
##
## Point est. Upper C.I.
## LDevsum 1 1.01
## dl0 1 1.00
## dl1 1 1.00
##
## Multivariate psrf
##
## 1
3.3 ACF Plots
Here we plotted ACF plots for the following variables:
- Total deviance;
- Variables that didn’t pass the convergence check.
3.4 WAIC results
| L1 | |
|---|---|
| DIC | 22743.872 |
| DIC3 | 22831.298 |
| PWAIC | 327.414 |
| WAIC | 22867.632 |